Gotowe bibliografie tematyczne / Oligonucleotide microarray

Gotowa bibliografia na temat „Oligonucleotide microarray”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 1 lutego 2022

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Artykuły w czasopismach na temat "Oligonucleotide microarray"

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Kyselková, M., J. Kopecký, M. Ságová-Marečková, G. L. Grundmann i Y. Moënne-Loccoz. "Oligonucleotide microarray methodology for taxonomic and functional monitoringof microbial community composition". Plant, Soil and Environment 55, No. 9 (14.10.2009): 379–88. http://dx.doi.org/10.17221/140/2009-pse.

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Microarray analysis is a cultivation-independent, high-throughput technology that can be used for direct and simultaneous identification of microorganisms in complex environmental samples. This review summarizes current methodologies for oligonucleotide microarrays used in microbial ecology. It deals with probe design, microarray manufacturing, sample preparation and labeling, and data handling, as well as with the key features of microarray analysis such as specificity, sensitivity and quantification potential. Microarray analysis has been validated as an effective approach to describe the composition and dynamics of taxonomic and functional microbial communities, in environments including soil, compost, sediment, air or humans. It is now part of the technical arsenal available to address key issues in microbial community ecology, ranging from biogeography to ecosystem functioning.
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Chizhikov, Vladimir, Avraham Rasooly, Konstantin Chumakov i Dan D. Levy. "Microarray Analysis of Microbial Virulence Factors". Applied and Environmental Microbiology 67, nr 7 (1.07.2001): 3258–63. http://dx.doi.org/10.1128/aem.67.7.3258-3263.2001.

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ABSTRACT Hybridization with oligonucleotide microchips (microarrays) was used for discrimination among strains of Escherichia coli and other pathogenic enteric bacteria harboring various virulence factors. Oligonucleotide microchips are miniature arrays of gene-specific oligonucleotide probes immobilized on a glass surface. The combination of this technique with the amplification of genetic material by PCR is a powerful tool for the detection of and simultaneous discrimination among food-borne human pathogens. The presence of six genes (eaeA, slt-I,slt-II, fliC, rfbE, andipaH) encoding bacterial antigenic determinants and virulence factors of bacterial strains was monitored by multiplex PCR followed by hybridization of the denatured PCR product to the gene-specific oligonucleotides on the microchip. The assay was able to detect these virulence factors in 15 Salmonella,Shigella, and E. coli strains. The results of the chip analysis were confirmed by hybridization of radiolabeled gene-specific probes to genomic DNA from bacterial colonies. In contrast, gel electrophoretic analysis of the multiplex PCR products used for the microarray analysis produced ambiguous results due to the presence of unexpected and uncharacterized bands. Our results suggest that microarray analysis of microbial virulence factors might be very useful for automated identification and characterization of bacterial pathogens.
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Russell, R. "Designing microarray oligonucleotide probes". Briefings in Bioinformatics 4, nr 4 (1.01.2003): 361–67. http://dx.doi.org/10.1093/bib/4.4.361.

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Zhang, Yongqing, Antonio Ferreira, Cheng Cheng, Yongchun Wu i Jiong Zhang. "Modeling Oligonucleotide Microarray Signals". Applied Bioinformatics 5, nr 3 (2006): 151–60. http://dx.doi.org/10.2165/00822942-200605030-00003.

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Koslov, I. A., F. Kaper, L. Zhou i M. S. Chee. "Microarray based oligonucleotide synthesis". Nucleic Acids Symposium Series 52, nr 1 (1.09.2008): 723. http://dx.doi.org/10.1093/nass/nrn365.

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Lehner, Angelika, Alexander Loy, Thomas Behr, Helga Gaenge, Wolfgang Ludwig, Michael Wagner i Karl-Heinz Schleifer. "Oligonucleotide microarray for identification ofEnterococcusspecies". FEMS Microbiology Letters 246, nr 1 (maj 2005): 133–42. http://dx.doi.org/10.1016/j.femsle.2005.04.002.

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Goji, Noriko, Trevor MacMillan i Kingsley Kwaku Amoako. "A New Generation Microarray for the Simultaneous Detection and Identification ofYersinia pestisandBacillus anthracisin Food". Journal of Pathogens 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/627036.

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The use of microarrays as a multiple analytic system has generated increased interest and provided a powerful analytical tool for the simultaneous detection of pathogens in a single experiment. A wide array of applications for this technology has been reported. A low density oligonucleotide microarray was generated from the genetic sequences ofY. pestisandB. anthracisand used to fabricate a microarray chip. The new generation chip, consisting of 2,240 spots in 4 quadrants with the capability of stripping/rehybridization, was designated as “Y-PESTIS/B-ANTHRACIS 4x2K Array.” The chip was tested for specificity using DNA from a panel of bacteria that may be potentially present in food. In all, 37 uniqueY. pestis-specific and 83B. anthracis-specific probes were identified. The microarray assay distinguishedY. pestisandB. anthracisfrom the other bacterial species tested and correctly identified theY. pestis-specific oligonucleotide probes using DNA extracted from experimentally inoculated milk samples. Using a whole genome amplification method, the assay was able to detect as low as 1 ng genomic DNA as the start sample. The results suggest that oligonucleotide microarray can specifically detect and identifyY. pestisandB. anthracisand may be a potentially useful diagnostic tool for detecting and confirming the organisms in food during a bioterrorism event.
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Kingsley, Mark T., Timothy M. Straub, Douglas R. Call, Don S. Daly, Sharon C. Wunschel i Darrell P. Chandler. "Fingerprinting Closely Related Xanthomonas Pathovars with Random Nonamer Oligonucleotide Microarrays". Applied and Environmental Microbiology 68, nr 12 (grudzień 2002): 6361–70. http://dx.doi.org/10.1128/aem.68.12.6361-6370.2002.

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ABSTRACT Current bacterial DNA-typing methods are typically based on gel-based fingerprinting methods. As such, they access a limited complement of genetic information and many independent restriction enzymes or probes are required to achieve statistical rigor and confidence in the resulting pattern of DNA fragments. Furthermore, statistical comparison of gel-based fingerprints is complex and nonstandardized. To overcome these limitations of gel-based microbial DNA fingerprinting, we developed a prototype, 47-probe microarray consisting of randomly selected nonamer oligonucleotides. Custom image analysis algorithms and statistical tools were developed to automatically extract fingerprint profiles from microarray images. The prototype array and new image analysis algorithms were used to analyze 14 closely related Xanthomonas pathovars. Of the 47 probes on the prototype array, 10 had diagnostic value (based on a chi-squared test) and were used to construct statistically robust microarray fingerprints. Analysis of the microarray fingerprints showed clear differences between the 14 test organisms, including the separation of X. oryzae strains 43836 and 49072, which could not be resolved by traditional gel electrophoresis of REP-PCR amplification products. The proof-of-application study described here represents an important first step to high-resolution bacterial DNA fingerprinting with microarrays. The universal nature of the nonamer fingerprinting microarray and data analysis methods developed here also forms a basis for method standardization and application to the forensic identification of other closely related bacteria.
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GERHOLD, DAVID, MEIQING LU, JIAN XU, CHRISTOPHER AUSTIN, C. THOMAS CASKEY i THOMAS RUSHMORE. "Monitoring expression of genes involved in drug metabolism and toxicology using DNA microarrays". Physiological Genomics 5, nr 4 (27.04.2001): 161–70. http://dx.doi.org/10.1152/physiolgenomics.2001.5.4.161.

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Oligonucleotide DNA microarrays were investigated for utility in measuring global expression profiles of drug metabolism genes. This study was performed to investigate the feasibility of using microarray technology to minimize the long, expensive process of testing drug candidates for safety in animals. In an evaluation of hybridization specificity, microarray technology from Affymetrix distinguished genes up to a threshold of ∼90% DNA identity. Oligonucleotides representing human cytochrome P-450 gene CYP3A5 showed heterologous hybridization to CYP3A4 and CYP3A7 RNAs. These genes could be clearly distinguished by selecting a subset of oligonucleotides that hybridized selectively to CYP3A5. Further validation of the technology was performed by measuring gene expression profiles in livers of rats treated with vehicle, 3-methylcholanthrene (3MC), phenobarbital, dexamethasone, or clofibrate and by confirming data for six genes using quantitative RT-PCR. Responses of drug metabolism genes, including CYPs, epoxide hydrolases ( EHs), UDP-glucuronosyl transferases ( UGTs), glutathione sulfotransferases ( GSTs), sulfotransferases ( STs), drug transporter genes, and peroxisomal genes, to these well-studied compounds agreed well with, and extended, published observations. Additional gene regulatory responses were noted that characterize metabolic effects or stress responses to these compounds. Thus microarray technology can provide a facile overview of gene expression responses relevant to drug metabolism and toxicology.
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Ali Syed, Haider, i David W. Threadgill. "Enhanced oligonucleotide microarray labeling and hybridization". BioTechniques 41, nr 6 (grudzień 2006): 685–86. http://dx.doi.org/10.2144/000112290.

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Rozprawy doktorskie na temat "Oligonucleotide microarray"

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Li, Xiaopeng. "Development of Oligonucleotide Microarray for High Throughput DNA Methylation Analysis". Cleveland State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=csu1224605179.

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Van, Zuydam Natalie Rachel. "Identification of Leptographium species by oligonucleotide discrimination on a DNA microarray". Diss., University of Pretoria, 2009. http://hdl.handle.net/2263/28928.

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Leptographium is an anamorph genus within the Ophiostomatoid group of fungi and represents a unique case for molecular applications. The genus has a near complete sequence data available for three genes across all known species. This characteristic makes it a perfect test group for investigating applications of new diagnostic techniques within ascomycetes. Probes and primers, for microarrays, are designed from phylogenetically useful gene regions and are fabricated onto a solid substrate using printing technology. The sample is prepared using PCR and is hybridised to the probes under stringent conditions. The resulting fluorescent pattern is rigorously analysed to distinguish species from each other. Diagnostic PCR uses primers that are designed in similar way to the way probes are designed for microarrays and indicate the presence of a species through positive amplification. This research methodology will be applied to Leptographium to evaluate the efficacy of microarray technology for discriminating species within that genus. The data gained from this research study will be used in applications for other genera using microarray technology.
Dissertation (MSc)--University of Pretoria, 2011.
Genetics
Unrestricted
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Broto, Avilés Marta. "Universal diagnostic platforms based on oligonucleotide codified nanoparticles and DNA microarray devices". Doctoral thesis, Universitat de Barcelona, 2017. http://hdl.handle.net/10803/462828.

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La medicina personalitzada esta prenent rellevància últimament. Aquesta es basa en la monitorització simultània de diferents biomarcadors, els biomarcadors poden ser molècules de diferent naturalesa química. Aquest fet fa palesa la necessitat de desenvolupar aproximacions tecnològiques universals per al diagnòstic capaces de detectar aquests biomarcadors independentment de la seva naturalesa química. En aquests context, la principal finalitat del projecte és el desenvolupament d’una plataforma bioanalítica per al diagnòstic in vitro que sigui multiplexada (per més de un biomarcador) i multimodal (per biomarcadors de diferent naturalesa química). L’aproximació proposada pretén traduir qualsevol interacció biomolecular (biomarcador- bioreceptor) en una senyal amplificada d’ADN que serà finalment detectada en un bioxip d’ADN. Aquesta estratègia s’anomena biobarcode. Com a prova de concepte de l’aproximació proposada ens hem centrat en la detecció de biomarcadors relacionats amb les malalties cardiovasculars (CVDs) i, també, en fàrmacs relacionats amb el càncer. CVDs són la principal causa de mort al món i inclouen un grup de desordres dels vasos coronaris i sanguinis. La detecció multiplexada i multimodal d’aquests biomarcadors podria ser de gran ajuda en el monitoratge de l’estat del pacient. Per altra banda, la segona causa de mort al món és el càncer, els fàrmacs utilitzats per tractar-lo s’anomenen cytostatics. La proximitat de la dosi tòxica i terapèutica dels fàrmacs cytostatics fa el monitoratge terapèutic dels fàrmacs (TDM) la clau per la optimització del tractament del càncer. Podem assumir que la monitorització del fàrmac juntament amb certs metabòlits milloraria la eficàcia i tolerabilitat, reduint la toxicitat.
Personalized therapy has become a crucial issue lately. It should be based on the simultaneous monitoring of different biomarkers which might include molecules of different chemical nature. This fact, calls for developing universal technological diagnostic approaches, able to determine these biomarkers, independently from their chemical nature, while modulating the necessary amplification factor. In this context, the aim of the project is to develop of a universal, multiplexed (for several biomarkers) and multimodal (biomarkers of different chemical nature) in vitro diagnostic bioanalytical platform. The proposed approach (Figure 1) pretends to translate any type of biomolecular interaction (bioreceptor-biomarker) into a PCR-less DNA amplification process that is finally detected on a DNA-microarray biosensor platform. This strategy is called biobarcode assay. As proof-of-concept of the proposed approach, we have focused on the detection of biomarkers related to cardiovascular diseases (CVDs) and, also, drugs related to cancer disease. CVDs are the main cause of death in the world and include a group of disorders of the heart and blood vessels, multimodal and multiplexed detection of CVDs-related biomarkers would help the monitoring of patient status. Otherwise, the second cause of death worldwide is cancer; drugs used to treat cancer are called cytostatics. Closely levels of therapeutic and toxic doses of cytostatics make therapeutic drug monitoring the milestone for the optimization of cancer treatment. It can be assumed that monitoring of drug concentration jointly with main metabolites should improve efficacy and tolerability and reduce toxicity. The main objective of the project will consist on demonstrating that it is possible to analyze targets of different chemical nature, and that the amplification can be modulated by varying the charge of oligonucleotides covalently attached to the nanoparticles.
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Black, Ryan Weldon. "Design and Evaluation of Oligonucleotide Microarrays for the Detection of Bovine Pathogens". DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/381.

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Two microarray designs were developed and produced to screen for multiple bovine pathogens commonly found in the cattle industry today. The first microarray was designed, built, and processed in-house using conventional material and equipment and targeted Pasteurella multocida, Manheimia haemolytica, Histophilus somni, and Arcanobacterium pyogenes. For each pathogen, 12 perfect-match oligonucleotide probes, which were also designed in-house, targeted different sections of the respective 16S ribosomal genes, and were coupled with 12 corresponding mismatched probes for background. These arrays were able to produce distinct hybridization patterns for each pathogen that were easily visible without the need for computer analysis. However, the need for PCR amplification of the 16S gene prior to hybridization motivated us to explore more efficient array options. The second designed microarray, a custom Affymetrix GeneChip, targeted Escherichia coli, Salmonella typhimurium, and Salmonella dublin in addition to the previously mentioned pathogens and was more successful in overall performance than the "in-house" arrays. In addition to the 16S gene, oligonucleotide probes targeted other genes (from 2 to >4500, depending on whether the genome was sequenced) that were unique to each pathogen. This array also differed from the "in-house" arrays in that mismatched probes were not designed. The different probe sets performed at different detection limits as P. multocida, A. pyogenes, S. typhimurium, and S. dublin were detected with as little as 250ng of hybridized genomic DNA (gDNA), while M. haemolytica, H. somni, and E. coli required as much as 1μg gDNA. These pathogens were also spiked into bovine tissue to simulate multiorgan infections in which they were individually detected with the microarray design.
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Nordberg, Eric Kinsley. "Creating Scientific Software, with Application to Phylogenetics and Oligonucleotide Probe Design". Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/64366.

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The demands placed on scientific software are different from those placed on general purpose software, and as a result, creating software for science and for scientists requires a specialized approach. Much of software engineering practices have developed in situations in which a tool is desired to perform some definable task, with measurable and verifiable outcomes. The users and the developers know what the tool "should" do. Scientific software often uses unproven or experimental techniques to address unsolved problems. The software is often run on "experimental" High Performance Computing hardware, adding another layer of complexity. It may not be possible to say what the software should do, or what the results should be, as these may be connected to very scientific questions for which the software is being developed. Software development in this realm requires a deep understanding of the relevent scientific domain area. The present work describes applications resulting from a scientific software development process that builds upon detailed understanding of the scientific domain area. YODA is an application primarily for selecting microarray probe sequences for measuring gene expression. At the time of its development, none of the existing programs for this task satisfied the best-known requirements for microarray probe selection. The question of what makes a good microarray probe was a research area at the time, and YODA was developed to incorporate the latest understanding of these requirements, drawn from the research literature, into a tool that can be used by a research biologist. An appendix examines the response and use in the years since YODA was released. PEPR is a software system for inferring highly resolved whole-genome phylogenies for hundreds of genomes. It encodes a process developed through years of research and collaboration to produce some of the highest quality phylogenies available for large sets of bacterial genomes, with no manual intervention required. This process is described in detail, and results are compared with high quality results from the literature to show that the process is at least as successful as more labor-intensive manual efforts. An appendix presents additional results, including high quality phylogenies for many bacterial Orders.
Ph. D.
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Benoit, Marie-Helene. "Oligonucleotide microarray analysis of chromosome-X gene expression in human epithelial ovarian cancer cell lines". Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81597.

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Microarray expression analysis was applied as an approach for identifying cancer-related genes on chromosome-X (CHR-X) in epithelial ovarian cancer (EOC). The Hu6800 and U133A GeneChipsRTM were used to evaluate the expression of 446 CHR-X genes in an in vitro EOC model system comprising 4 EOC cell lines and 12 primary cultures of normal ovary surface epithelia. Fifty-one new candidate CHR-X genes were identified in addition to 49 genes previously implicated in cancer. Many genes map to regions with frequent genetic aberrations in EOC tumours, or interact with the known EOC tumour suppressors BRCA1 and BRCA2. Candidate genes described in this study may provide novel markers for histopathological subtypes, or the tumourigenic potential of EOC tumours. The X-inactive-specific-transcript (XIST) was absent in two highly tumourigenic EOC cell lines, TOV21G and TOV112D. XIST mRNA is important for the stability of X-chromosome-inactivation (XCI), as its absence destabilizes the silencing of genes on the inactive-X. Aberrant bi-allelic expression of FHL1, a gene subjected to XCI was detected in the cell line TOV21G but not in the cell line TOV112D. Genotyping assays using polymorphic microsattelite markers suggested that TOV21G has retained heterozygosity of CHR-X. The majority of alleles tested for TOV112D were consistent with loss of heterozygosity of CHR-X. Taken together these findings are consistent with two proposed mechanisms mediating XIST loss-of-expression in cancer: (1) Duplication of the active-X followed by loss of the inactive-X (TOV112D); or (2) Reactivation of the previously inactive-X (TOV21G).
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Jeong, Sooyoung. "A custom oligonucleotide microarray analysis as a tool for dissecting soybean-bradyrhizobium japonicum nodule senescence". Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/6266.

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Thesis (M.S.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on May 27, 2009) Includes bibliographical references.
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Gusnanto, Arief. "Regression on high-dimensional predictor space : with application in chemometrics and microarray data /". Stockholm, 2004. http://diss.kib.ki.se/2004/91-7140-153-9/.

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Wennmalm, Kristian. "Analytical strategies for identifying relevant phenotypes in microarray data /". Stockholm, 2007. http://diss.kib.ki.se/2007/978-91-7357-401-3/.

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Xue-Franzén, Yongtao. "DNA microarray approaches to understanding the regulation and evolution of gene expression networks". Stockholm : Huddinge : Karolinska institutet ; Södertörns högskola, 2009. http://diss.kib.ki.se/2009/978-91-7409-554-8/.

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Książki na temat "Oligonucleotide microarray"

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Knudsen, Steen. Guide to Analysis of DNA Microarray Data. New York: John Wiley & Sons, Ltd., 2005.

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Steen, Knudsen, red. Guide to analysis of DNA microarray data. Wyd. 2. Hoboken, N.J: Wiley-Liss, 2004.

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Zidong, Wang, i Liu Xiaohui, red. Microarray image analysis: An algorithmic approach. Boca Raton, FL: Chapman & Hall/CRC, 2010.

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Microarray analysis. Hoboken, NJ: Wiley-Liss, 2003.

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Dongguang, Li, red. DNA microarray technology and data analysis in cancer research. Singapore: World Scientific, 2008.

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Javier, Cabrera, red. Exploration and analysis of DNA microarray and protein array data. Hoboken, NJ: John Wiley, 2004.

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Applying genomic and proteomic microarray technology in drug discovery. Boca Raton: CRC Press, 2005.

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T, Kho Alvin, i Butte Atul J, red. Microarrays for an integrative genomics. Cambridge, Mass: MIT Press, 2003.

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Thomas, Roeder, red. Microarrays. Burlington, MA: Elsevier Academic Press, 2006.

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Muller, Hans-Joachim. Microarrays. Burlington, MA: Elsevier Academic Press, 2005.

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Części książek na temat "Oligonucleotide microarray"

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De Carvalho, Sérgio A., i Sven Rahmann. "Algorithms for Oligonucleotide Microarray Layout". W Bioinformatics Algorithms, 277–301. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470253441.ch13.

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Kim, Young H., i Jonathan R. Pollack. "Comparative Genomic Hybridization on Spotted Oligonucleotide Microarrays". W Microarray Analysis of the Physical Genome, 21–32. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-192-9_3.

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Lucito, Robert, i James Byrnes. "Comparative Genomic Hybridization by Representational Oligonucleotide Microarray Analysis". W Microarray Analysis of the Physical Genome, 33–46. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-192-9_4.

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Malutan, Raul, Pedro Gómez i Monica Borda. "Oligonucleotide Microarray Probe Correction by FixedPoint ICA Algorithm". W Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 988–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_150.

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Barros, Eugenia. "Identification of Mycotoxigenic Fungi Using an Oligonucleotide Microarray". W Laboratory Protocols in Fungal Biology, 529–34. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-2356-0_52.

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Pullat, Janne, i Andres Metspalu. "Arrayed Primer Extension Reaction for Genotyping on Oligonucleotide Microarray". W Prenatal Diagnosis, 161–67. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-066-9_12.

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Sipe, Conor W., Vijay R. Dondeti i Margaret S. Saha. "In Silico Gene Selection for Custom Oligonucleotide Microarray Design". W Methods in Molecular Biology, 417–28. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-304-2_26.

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Eeckhoute, Jérôme, Mathieu Lupien i Myles Brown. "Combining Chromatin Immunoprecipitation and Oligonucleotide Tiling Arrays (ChIP-Chip) for Functional Genomic Studies". W Microarray Analysis of the Physical Genome, 155–64. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-192-9_11.

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Fassbender, Anne, Jörn Lewin, Thomas König, Tamas Rujan, Cecile Pelet, Ralf Lesche, Jürgen Distler i Matthias Schuster. "Quantitative DNA Methylation Profiling on a High-Density Oligonucleotide Microarray". W Methods in Molecular Biology, 155–70. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-545-9_9.

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Filippone, Maurizio, Francesco Masulli, Stefano Rovetta, Sushmita Mitra i Haider Banka. "Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis". W Computational Methods in Systems Biology, 312–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11885191_22.

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Streszczenia konferencji na temat "Oligonucleotide microarray"

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Lu, Zu-Hong, Yujie Zhao, Nongyao He i Xiao Sun. "Design and on-chip synthesis technology of oligonucleotide microarray". W Optics and Optoelectronic Inspection and Control: Techniques, Applications, and Instruments, redaktorzy Hong Liu i Qingming Luo. SPIE, 2000. http://dx.doi.org/10.1117/12.403955.

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Hou, Peng, Meiju Ji, Nongyao He i Zuhong Lu. "Methylation oligonucleotide microarray: a novel tool to analyze methylation patterns". W Microtechnologies for the New Millennium 2003, redaktorzy Angel Rodriguez-Vazquez, Derek Abbott i Ricardo Carmona. SPIE, 2003. http://dx.doi.org/10.1117/12.497693.

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Wang, Lili, Alioune Ngom i Robin Gras. "Non-unique oligonucleotide microarray probe selection method based on genetic algorithms". W 2008 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2008. http://dx.doi.org/10.1109/cec.2008.4630919.

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Duan, Liang, Yonghui Song, Siqing Xia, Slawomir W. Hermanowicz, Fangming Jin, Qi Zhou i Bing Wu. "Detection of microbial communities in continuous and discontinuous membrane bioreactor using high-density oligonucleotide Microarray". W 2nd International Symposium on Aqua Science, Water Resource and Low Carbon Energy. AIP, 2010. http://dx.doi.org/10.1063/1.3529266.

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Huang, Chi-Cheng, Chao-Chiang Tu, Mong-Hsun Tsai, Liang-chuan Lai i Ching-Shui Huang. "Abstract 2481: Concordance of PAM50 molecular subtyping between oligonucleotide microarray and nanoString nCounter assay for Taiwanese breast cancer". W Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-2481.

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McArthur, HL, LK Tan, S. Patil, M. Wigler, CA Hudis, J. Hicks i L. Norton. "High resolution representational oligonucleotide microarray analysis (ROMA) suggests that TOPO2 and HER2 co-amplification is uncommon in human breast cancer." W CTRC-AACR San Antonio Breast Cancer Symposium: 2008 Abstracts. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/0008-5472.sabcs-2023.

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Li, Jiong, Hong Wang, Heping Liu, M. Zhang, Chunxiu Zhang, Zu-Hong Lu, Xiang Gao i Dong Kong. "Long synthetic oligonucleotides for microarray expression measurement". W International Conference on Sensing units and Sensor Technology, redaktorzy Yikai Zhou i Shunqing Xu. SPIE, 2001. http://dx.doi.org/10.1117/12.440169.

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Burden, C. J. "Intensity isotherms and distributions on oligonucleotide microarrays". W 2009 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2009. http://dx.doi.org/10.1109/cec.2009.4983335.

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Jaziri, Faouzi, David R. C. Hill, Nicolas Parisot, Jeremie Denonfoux, Eric Dugat-Bony, Eric Peyretaillade i Pierre Peyret. "MetaExploArrays: A Large-Scale Oligonucleotide Probe Design Software for Explorative DNA Microarrays". W 2012 13th International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT). IEEE, 2012. http://dx.doi.org/10.1109/pdcat.2012.94.

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Ono, Naoaki, Shingo Suzuki, Chikara Furusawa, Hiroshi Shimizu i Tetsuya Yomo. "Quantitative expression analysis using oligonucleotide microarrays based on a physico-chemical model". W 3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems. ICST, 2008. http://dx.doi.org/10.4108/icst.bionetics2008.4750.

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